Keyword Spotting

Follow this topic Ask about this topic

Momentum

1 paper in the last four weeks, with none the four weeks before. 0.0% of all new papers.

Jul 6Week of Sep 21

Latest papers 16

All topics

BaLEEN: Biasing with Latent Encoded Entities for Context-Aware ASR
Sep 29, 2026Chihiro Taguchi, Yotaro Kubo, Rujikorn CharakornAutomatic Speech Recognition Keyword Spotting
University of Notre Dame, Department of Computer Science and Engineering, IN, USA · Sakana AI, Tokyo, Japan
Sub-Model Short-Term Memory Convolutions for Keyword Spotting Systems on Device
Sep 28, 2026Paweł Warlewski, Artur Czeczko, Artur Szumaczuk +2Keyword Spotting Resource-Constrained Edge Devices
Samsung R&D Institute Poland · Samsung AI Center Warsaw
HPMD: A Historical Persian Manuscript Dataset for Word Spotting with Line-Level Annotation
Sep 28, 2026Saeid Firouzi Daghigh, Majid Iranpour MobarakehHistorical Manuscripts Persian
Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran
CircleMatch: Prototype Matching with Circular Temporal Statistics for Tiny Keyword Spotting
Sep 17, 2026Jiajun Sun, Zhe GaoKeyword Spotting Text Corpora
Shanghai Normal University, Shanghai, China
MMLDSum-LLM: Multimodal Long-Document Summarization with Visual-Alignment and Keyword-Aware
Jul 30, 2026Xianpeng Zhang, Jiahua Yang, Dongyu Chen +7Multimodal Large Language Models Multimodal Documents
OPPO Guangdong Mobile Telecommunications Co., Ltd.
Cumsum-Composable Phase Transport for Low-Cost Streaming Keyword Spotting
Jul 22, 2026Mahesh GodavartiKeyword Spotting Streaming
A Carrot, Inc
Scalable Keyword Spotting via Modular Network Expansion
Jul 22, 2026Viktor Khaymonenko, Dzmitry Saladukha, Aliaksei Rak +1Keyword Spotting Parameter-Efficient Adaptation
Embedded Voice Input Team, Yandex, Russia · Embedded Voice Input Team, Yandex, Belarus
Personalized Keyword Spotting for User-Defined Keywords Leveraging Text-Independent Speaker Verification
Jun 18, 2026Ming-Hsiang Hu, Kuan-Tang Huang, Chien-Chun Wang +2Keyword Spotting Automatic Speaker Verification
Dept. Computer Science and Information Engineering, National Taiwan Normal University, Taiwan · E.SUN Financial Holding Co., Ltd., Taiwan · United Link Co., Ltd., Taiwan
Connecting Speech to Words through Images
Jun 15, 2026Gabriel Pirlogeanu, Dan Oneata, Horia Cucu +1Keyword Spotting Unsupervised
Speech and Dialogue Research Laboratory · POLITEHNICA Bucharest, Romania · Electrical and Electronic Engineering +1
Stabilizing Short Duration Speaker Verification through Neural Re-scoring with Hybrid Enrollment
Jun 15, 2026Zhiqi Ai, Han Cheng, Shiyi Mu +3Automatic Speaker Verification Discrete Speech Representations
Shanghai University, China · Hithink RoyalFlush AI Research Institute, China · Xi’an Jiaotong-Liverpool University, China
Massive Open-Vocabulary Keyword Spotting
Jun 9, 2026Leonor Barreiros, Raul Monteiro, Afonso Mendes +1Keyword Spotting Automatic Speech Recognition
Priberam Labs, Lisboa, Portugal · Instituto Superior Técnico, Lisboa, Portugal · Instituto de Telecomunicações, Lisboa, Portugal
KFC-KWS: Keyframe Fusion with CTC for User-Defined Keyword Spotting
Jun 9, 2026Jin Li, Wenbin Jiang, Ji HuKeyword Spotting Grapheme-To-Phoneme
School of Electronics and Information Engineering, Hangzhou Dianzi University, Hangzhou, China · School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China
Effective User-defined Keyword Spotting with Dual-stage Matching, Multi-modal Enrollment, and Continual Adaptation
May 21, 2026Zhiqi Ai, Han Cheng, Shiyi Mu +3Keyword Spotting Automatic Speaker Verification
Shanghai University, Shanghai 200444, China · New York University, New York, NY 10012 USA · Xi’an Jiaotong-Liverpool University, Suzhou 215000, China
End-to-End Keyword Spotting on FPGA Using Graph Neural Networks with a Neuromorphic Auditory Sensor
May 10, 2026Wiktor Matykiewicz, Piotr Wzorek, Kamil Jeziorek +4Neuromorphic Computing Field-Programmable Gate Arrays
AGH University of Krakow, Poland · Embedded Vision Systems Group, Computer Vision Laboratory · Robotics and Technology of Computers Lab., ETSII, EPS, SCORE, I3US, Universidad de Sevilla
Beyond Retrieval: A Multitask Benchmark and Model for Code Search
May 6, 2026Siqiao Xue, Zihan Liao, Jin Qin +4Cross-Encoder Reranking Text Embeddings
Ant Group · Alipay
Keyword spotting using convolutional neural network for speech recognition in Hindi
Apr 26, 2026Saru Bharti, Pushparaj Mani PathakKeyword Spotting Spectral Features
iHub DivyaSampark Indian Institute of Technology, Roorkee Roorkee, India · Mechanical and Industrial Engineering Department Indian Institute of Technology, Roorkee Roorkee, India

Sep 29, 2026, cs.CLJ/K move · Enter open · S save

BaLEEN: Biasing with Latent Encoded Entities for Context-Aware ASR

Chihiro Taguchi, Yotaro Kubo, Rujikorn Charakorn

University of Notre Dame, Department of Computer Science and Engineering, IN, USA · Sakana AI, Tokyo, Japan

Automatic Speech Recognition Keyword Spotting Entities

Open paper AskPDF arXiv

Transcribing domain-specific entities and rare proper nouns remains a major challenge in automatic speech recognition (ASR). In this paper, we propose BaLEEN (Biasing with Latent Encoded Entities), a lightweight, hypernetwork-based framework for dynamic contextual adaptation without fine-tuning the underlying ASR model. BaLEEN encodes variable-length contextual keywords using a pretrained language model, compresses them into a fixed sequence of latent vectors via a Perceiver bottleneck, and injects context-dependent bias vectors directly into the intermediate encoder representations of the ASR model. Because both the language model and the backbone ASR model remain entirely frozen during training, BaLEEN operates as a plug-and-play adapter that incurs zero computational overhead at inference time when context biases are precomputed. We evaluate our method on a CTC-based ASR model using a Wikipedia-derived corpus with annotated named entities and synthetic speech. Experimental results demonstrate that BaLEEN reduces keyword miss rate by 8.7% on the test set relative to the unbiased baseline while simultaneously improving overall word error rate by 21% and character error rate by 28%.

Momentum

Related topics

Latest papers 16